8 research outputs found
Collagen Fiber Array of Peritumoral Stroma Influences Epithelial-to-Mesenchymal Transition and Invasive Potential of Mammary Cancer Cells
: Interactions of cancer cells with matrix macromolecules of the surrounding tumor stroma are critical to mediate invasion and metastasis. In this study, we reproduced the collagen mechanical barriers in vitro (i.e., basement membrane, lamina propria under basement membrane, and deeper bundled collagen fibers with different array). These were used in 3D cell cultures to define their effects on morphology and behavior of breast cancer cells with different metastatic potential (MCF-7 and MDA-MB-231) using scanning electron microscope (SEM). We demonstrated that breast cancer cells cultured in 2D and 3D cultures on different collagen substrates show different morphologies: i) a globular/spherical shape, ii) a flattened polygonal shape, and iii) elongated/fusiform and spindle-like shapes. The distribution of different cell shapes changed with the distinct collagen fiber/fibril physical array and size. Dense collagen fibers, parallel to the culture plane, do not allow the invasion of MCF-7 and MDA-MB-231 cells, which, however, show increases of microvilli and microvesicles, respectively. These novel data highlight the regulatory role of different fibrillar collagen arrays in modifying breast cancer cell shape, inducing epithelial-to-mesenchymal transition, changing matrix composition and modulating the production of extracellular vesicles. Further investigation utilizing this in vitro model will help to demonstrate the biological roles of matrix macromolecules in cancer cell invasion in vivo
Substrate Type and Concentration Differently Affect Colon Cancer Cells Ultrastructural Morphology, EMT Markers, and Matrix Degrading Enzymes
: Aim of the study was to understand the behavior of colon cancer LoVo-R cells (doxorubicin-resistant) vs. LoVo-S (doxorubicin sensitive) in the initial steps of extracellular matrix (ECM) invasion. We investigated how the matrix substrates Matrigel and type I collagen-mimicking the basement membrane (BM) and the normal or desmoplastic lamina propria, respectively-could affect the expression of epithelial-to-mesenchymal transition (EMT) markers, matrix-degrading enzymes, and phenotypes. Gene expression with RT-qPCR, E-cadherin protein expression using Western blot, and phenotypes using scanning electron microscopy (SEM) were analyzed. The type and different concentrations of matrix substrates differently affected colon cancer cells. In LoVo-S cells, the higher concentrated collagen, mimicking the desmoplastic lamina propria, strongly induced EMT, as also confirmed by the expression of Snail, metalloproteases (MMPs)-2, -9, -14 and heparanase (HPSE), as well as mesenchymal phenotypes. Stimulation in E-cadherin expression in LoVo-S groups suggests that these cells develop a hybrid EMT phenotype. Differently, LoVo-R cells did not increase their aggressiveness: no changes in EMT markers, matrix effectors, and phenotypes were evident. The low influence of ECM components in LoVo-R cells might be related to their intrinsic aggressiveness related to chemoresistance. These results improve understanding of the critical role of tumor microenvironment in colon cancer cell invasion, driving the development of new therapeutic approaches
Numerical Simulation of JCO-E Pipe Manufacturing Process and Its Effect on the External Pressure Capacity of the Pipe
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe
Extracellular Matrix-Mediated Breast Cancer Cells Morphological Alterations, Invasiveness, and Microvesicles/Exosomes Release.
Breast cancer is a leading disease in women. Several studies are focused to evaluate the critical role of extracellular matrix (ECM) in various biochemical and molecular aspects but also in terms of its effect on cancer cell morphology and therefore on cancer cell invasion and metastatic potential. ECM fibrillar components, such as collagen and fibronectin, affect cell behavior and properties of mammary cancer cells. The aim of this study was to investigate using the scanning electron microscopy (SEM) how the highly invasive MDA-MB-231 breast cancer cells, interplaying with ECM substrates during cell migration/invasion, modify their morphological characteristics and cytoplasmic processes in relation to their invasive potential. In particular we reproduced and analyzed how natural structural barriers to cancer cell invasion, such as the basement membrane (Matrigel) and fibrillar components of dermis (fibronectin as well as the different concentrations/array of type I collagen), could induce morphological changes in 3D cultures. Interestingly, we demonstrate that, even with different effects, all collagen concentrations/arrays lead to morphological alterations of breast cancer cells. Intriguingly, the elongated mesenchymal shaped cells were more prominent in 3D cultures with a dense and thick substrate (thick Matrigel, high concentrated collagen network, and densely packed collagen fibers), even though cells with different shape produced and released microvesicles and exosomes as well. It is therefore evident that the peri-tumoral collagen network may act not only as a barrier but also as a dynamic scaffold which stimulates the morphological changes of cancer cells, and modulates tumor development and metastatic potential in breast cancer
Basement Membrane, Collagen, and Fibronectin: Physical Interactions with Cancer Cells
Cancer cell invasion is regulated by extracellular matrix (ECM) chemical signaling and gene expression but it also consists in a mechanical process controlled by ECM’s array. Scanning electron microscope analysis, invasion test, and real-time PCR demonstrated that Matrigel mimicking basement membrane (BM) doesn’t promote epithelial–mesenchymal transition (EMT) in both low and very aggressive breast cancer cells (MCF-7 and MDA-MB-231). A loose network of type I collagen mimicking the sub-BM favors EMT in MCF-7 cells but physically limits their invasion ability vs. Matrigel, as collagen does not induce an increase of metalloproteases (MMPs) in cells following ameboid-invasion mode. Collagen doesn’t change MDA-MB-231 phenotypes but further improves their invasion capability vs. Matrigel, by stimulating MMPs production. Concentrated type I collagen mimicking deeper ECM induces cells adhesion, further development of microvesicles, microvilli, long filopodia, and tunneling nanotubes (TNTs). Nonaligned fibronectin favors breast cancer cells adhesion, microvesicles, and TNTs development. Densely packed and parallel collagen fibers mimicking a collagen array in mammary tumor progression oppose invasion. In colon cancer, LoVo-R cells, resistant to doxorubicin, concentrated collagen favors development of invaginating phenotypes with invadopodia. We suggest that collagen acts as a physical factor inducing EMT in breast cancer cells and drug resistance in LoVo-R cells
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Large expert-curated database for benchmarking document similarity detection in biomedical literature search
Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical science. © The Author(s) 2019. Published by Oxford University Press